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Study On Control Of Inverted Pendulum With Particle Swarm Optimization Algorithm

Posted on:2009-01-25Degree:MasterType:Thesis
Country:ChinaCandidate:X G CengFull Text:PDF
GTID:2178360245489494Subject:Control theory and control engineering
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The inverted pendulum system is a typical single input and multiple outputs,nonlinear,high order,natural unstable system. Research on the accurate control of the inverted pendulum not only reflects several joints-in control theory,such as,nonlinear problems,robustness,as well as tracking,but also has great engineering value to the complex industrial objects.Recently,Particle Swarm Optimization(PSO)algorithm comes forth as another intelligent algorithm.It is simple with concept, parameters and implementation.Inverted pendulum,PSO and its researchment actuality are summarized firstly,then PSO is applied to optimize and design the control systems.The main contributions given in this dissertation are as follows:(1)Using Newton's mechanicstheory to establish the linear level inverted pendulum mathematical model.LQR(Linear Quadratic Regulator)controller in modern control theory is designed,and simulation performances are given by MATLAB7.0.(2)PSO is proposed to optimize the parameters of the conventional PID controller.The simulation results of the different control systems show that the optimal PIP controller based on PSO has a satisfying performance and is better than the conventional PID controller based on the conventional.(3)PSO algorithm is used to train the weights and the thresholds of Multilayer Feedforward Neural Networks(MFNN)instead of Back Propagation(BP)algorithm.The NN trained by PSO is applied to identify non-linear function and pattern recognition.The experimental results show that the proposed method is effective but low-precision than BP algorithm.To improve the global searching capability of PSO,the concept of 'Particle Swarm Exploding' is introduced into the PSO,experimental results show that the proposed method is effective.The hybrid algorithm combining PSO algorithm with BP algorithm is used to train the MFNN.Defects of conventional BP algorithm,i.e.the slow convergence of weight and threshold learning,premature result,and the slow training speed of PSO,are settled by it.(4)A NNC(Neural Network Controller)is made based on PSO algorithm to control inverted pendulum and theexperiment results prove the good effectiveness of NNC method based on PSO.Finally some conclusions and future researches are drawn in this dissertation.
Keywords/Search Tags:Inverted Pendulum, Particle Swarm Optimization algorithm, BP Neural Networks, PID controller
PDF Full Text Request
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